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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Which statement is true for negative binomial and Poisson regression models?

A) Poisson regression is a special case of negative binomial regression.
B) Negative binomial models accommodate negative integers while Poisson regression does not.
C) Poisson regression models are used for count data, and negative binomial models are used for binary responses.
D) The canonical link function for Poisson regression is the log, while for negative binomial it is the logit.

2. Refer to the exhibits:
Exhibit 1:

Exhibit 2:

An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.
Why are there 5 cluster IDs in Exhibit 2 based on these settings?

A) Cluster Matrix Visible Roles setting is 5.
B) Parallel Coordinates Visible Roles setting is 5.
C) There are observations with missing values.
D) Variable Standardization has been chosen.

3. Cluster Analysis in SAS Visual Statistics is categorized as which type of machine learning?

A) Supervised learning
B) Semi-supervised learning
C) Reinforcement learning
D) Unsupervised learning

4. What are decision tree properties that can be defined during model construction?

A) The number of neighbors in a k-nearest neighbors model
B) The maximum depth of the tree
C) The minimum number of data points in a leaf node
D) The learning rate for gradient boosting

5. Refer to the fit summary from SAS Visual Statisitcs in the exhibit below.

What can be concluded from the fit summary?

A) Customer Value Level C has no important variables associated with it.
B) Average Sales is an important predictor when Customer Value Level = C.
C) Average Sales is a significant predictor when Customer Value Level = E.
D) Customer Value Level is not a significant predictor in this model.

Solutions: